Optimal Innovation-Based Deception Attacks on Multi-Channel Cyber–Physical Systems
Year: 2025
Type: article
Abstract: This article addresses the optimal scheduling problem for linear deception attacks in multi-channel cyber–physical systems. The scenario where the attacker can only attack part of the channels due to energy constraints is considered. The effectiveness and stealthiness of attacks are quantified using state estimation error and Kullback–Leibler divergence, respectively. Unlike existing strategies relying on zero-mean Gaussian distributions, we propose a generalized attack model with Gaussian distributions characterized by time-varying means. Based on this model, an optimal stealthy attack strategy is designed to maximize remote estimation error while ensuring stealthiness. By analyzing correlations among variables in the objective function, the solution is decomposed into a semi-definite programming problem and a 0–1 programming problem. This approach yields the modified innovation and an attack scheduling matrix. Finally, numerical simulations validate the theoretical results.
Source: Electronics
Authors: Xinhe Yang, Zhu Ren, Jingquan Zhou, Jing Huang
Institution: Zhejiang Sci-Tech University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W4409439506